Some Basic Information You Should Know about Raw Data
This post mainly introduces raw data including its definition, main components, application, etc. You will have an overall understanding after reading the post.
What Is Raw Data
Raw data indicates tables of data where each row includes an observation and each column stands for a variable that explains some property of each observation. Raw data is also called tidy data, flat data, primary data, atomic data, and unit record data.
You need to note that raw data sometimes also refers to data that has not been processed. Given to that fact, it is considered as raw data. The information may be stored in a file or just a collection of numbers and characters are stored in some place on the hard disk. The following table tells you what raw data is.
-image from researchgate.net
The information entered into a database (either by a user or created by the computer itself) is called raw data. To know more information about raw data meaning, please keep reading this post of MiniTool.
What Consists of Raw Data
As mentioned above, raw data is a source of information for the Data Stream service that is used to deliver data resulting from cross-functional cooperation of integrated marketing systems. The systems contain the frequently used Demand Side Platform (DSP), Supply Side Platform (SSP), as well as data provider (DMP).
The data stream and raw data can be offered in a variety of formats. In each format, it has corresponding attributes according to the selected data to be received.
For instance, the data point format includes number of Data Point occurrences, last user’s activity, main user’s country, last timestamp, and cookie lifetimes.
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Here are 2 types of provided raw data streams (mobile apps data stream and desktop data stream). The mobile apps data stream, as implied by its name, is a raw data from mobile apps. Both the two types contain digital information related to users’ behavior and device.
Therefore, the raw data is an ideal source for data scientists. They can use it to set up custom segments for targeting online campaigns or make data analysis based on it.
The Application of Raw Data
The raw data can be used in multiple areas such as fraud detection & scoring, artificial intelligence, profiling & personalization, etc. As the raw data has not been processed, it is reliable. It can be used to data analysis and machine learning techniques.
The following are several fields that raw data is used to.
- Fraud detection & scoring: It can be used for anti-fraud algorithm. To be specific, timestamp, the number of cookie occurrences, or the data point analysis can be utilized within the scoring system to find fraud or to ensure that the message receiver is not a human.
- Artificial intelligence: The raw data can be used as a train set and test set when setting up machine learning algorithms.
- Profiling & personalization: You can customize client profiles and divide them for segmentation with the raw data.
- Business intelligence: The raw data can also be the source information for BI systems, which can enrich user profiles with the detailed information. It is a good material for business analyzing and performing predictive research.
- Target: Data scientists can boost online campaigns and reach the target audience under the help of raw data.
- CRM enrichment: The raw data can be integrated with the client’s CRM system so that the user profile gap can be filled. While enriching the CRM system enables clients to have a full view of their customers. Hence, they can send highly personalized messages.
The Bottom Line
Do you know what raw data definition is? Read here, you may have known the answer. In addition, you can get some additional information associated with raw data. For instance, you can learn the main components and main applications of raw data. Now, here comes the end of this post.